Triple

T7084841
Position Surface form Disambiguated ID Type / Status
Subject Munny Begum E165048 entity
Predicate title P38 FINISHED
Object Begum E106849 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Begum | Statement: [Munny Begum, title, Begum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Begum
Context triple: [Munny Begum, title, Begum]
  • A. Begum chosen
    Begum is an honorific title historically used in South Asia for Muslim women of high social rank, especially queens, princesses, and noblewomen.
  • B. Hazrat Begum
    Hazrat Begum was a Mughal princess who became one of the wives of Ahmad Shah Durrani, the founder of the Durrani Empire in Afghanistan.
  • C. Kandahari Begum
    Kandahari Begum was a Mughal princess and the first wife of Emperor Shah Jahan, known for her Timurid lineage and political significance in the Mughal court.
  • D. Khanzada Begum
    Khanzada Begum was a Timurid princess and elder sister of Mughal emperor Babur, noted for her political marriages and influential role in early Mughal diplomacy.
  • E. Haji Begum
    Haji Begum was a Mughal empress and chief consort of Emperor Humayun, best known for overseeing the construction of his grand mausoleum in Delhi.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c6887d98408190912b9580666b0c1d completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e511535c819098f60de54930380f completed March 27, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7948094ec8190856870dfd59fc13a completed March 28, 2026, 8:42 a.m.
Created at: March 27, 2026, 2:40 p.m.